Maternal diabetes and fracture risk in offspring: a population-based analysis
Bibliographic record
Abstract
Factors affecting intrauterine environment exerts influence on skeletal health and fracture risk in later life. Diabetes during pregnancy is known to influence birth weight and is associated with fetal overgrowth. However, the effects of maternal diabetes on fracture risk in offspring is unknown. This study was aimed to evaluate the association between maternal diabetes and fracture risk in offspring. Using population-based administrative health data for Manitoba, Canada, we identified deliveries complicated by gestational diabetes and type 2 diabetes between April 1, 1980, and March 31, 2020. The cohort was followed for a median of 15.8 yr. The primary outcome was any incident fracture in offspring. Secondary outcomes were long bone upper extremity fracture, long bone lower extremity fracture, vertebral fracture, and any non-trauma fractures. Cox proportional hazard regression models were used to estimate fracture risk in offspring by maternal diabetes status adjusted for relevant covariates. Of the 585 176 deliveries, 26 397 offspring were born to women with diabetes (3.0% gestational diabetes and 1.5% type 2 diabetes), and 558 779 were born to women without diabetes. The adjusted risk for any fracture was 7% (hazard ratio, 1.07; 95% CI, 2.7-11.5%) higher in the offspring of mothers with diabetes than offspring of mothers without diabetes. Types of fractures were similar between the 2 groups with a predominance of long bone upper extremity fractures. In conclusion, maternal diabetes was associated with a modest increase in fracture risk in offspring. Longitudinal prospective studies are needed to understand intrauterine and postnatal factors that may influence fracture risk in the offspring of mothers with diabetes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".